Asheesh “Danny” Singh, professor in agronomy, G.F. Sprague Chair in Agronomy and co-director of the Iowa Soybean Research Center, is the recipient of the faculty 2025 Outstanding Achievement in Research Award from the College of Agriculture and Life Sciences at Iowa State University. He is an exceptional scientist who has made transformative contributions to plant breeding, genetics and agricultural technology.
Singh leads an innovative research program integrating cutting-edge technologies, including artificial intelligence, robotics and high-throughput phenotyping to accelerate crop improvement and address critical global food security and agricultural sustainability issues. He has developed novel AI-enabled phenotyping pipelines that can rapidly and accurately assess complex traits like disease resistance, yield potential and stress tolerance. He leads the Soynomics team, where they are advancing machine learning and deep learning in agriculture. The team has pioneered hyperspectral imaging and vegetation indices for early detection of drought stress in soybeans.
His interdisciplinary approach to research is exemplified by his collaboration with engineers, computer scientists and agronomists. A colleague stated, “His ability to work across disciplines and translate basic research into practical applications for farmers is exceptional.” Singh is co-leading major multi-institutional initiatives, including a $20 million National Science Foundation AI Institute for Resilient Agriculture, focused on developing next-generation technologies for climate-resilient and sustainable crop improvement and management.
“Singh’s research productivity and impact are remarkable,” stated a colleague. Throughout his career, Singh has developed 21 soybean varieties and more than 40 wheat cultivars which are grown on 15 million acres annually, making him one of the world’s most prolific and successful public crop breeders. In addition to peer-reviewed papers and journal articles, Singh has co-authored a textbook on plant breeding and cultivar development. He is globally recognized for his work on applying machine learning and computer vision for high-throughput plant phenotyping in breeding, and has delivered more than 75 invited presentations in North America, South America, Europe, Asia and Australia.
Singh is deeply committed to training the next generation of scientists, as well. His innovative mentoring methods engage students in experiential learning and real world problem solving. His interdisciplinary approach integrates knowledge from agronomy, breeding, engineering and data analytics. He emphasizes real world relevance, connecting scientific concepts to societal challenges using cutting-edge technologies.